Urban Transportation System Resilience and Diversity Coupling using Large-scale Taxicab GPS Data

In this study, moving towards enabling the development of a platform for dynamic performance assessment of roadway networks, we have proposed to leverage coarse GPS data from probe vehicles such as taxis to quantify the resilience of road network using a multi-dimensional approach. The method is applied to a dataset of taxi trips in the Washington metropolitan area to analyze the roadways resilience to recurrent traffic jams during rush hours. Further, the influence of the diversity of transportation system, that quantifies the availability and distribution of transportation modes in an urban community, on the resilience of roadways to congestions is explored. The results indicate that the resilience of trips in all zones is highly correlated with the transportation diversity of those zones. Specifically, the pick-up and drop-off hubs of taxi trips in the District of Columbia are mainly located in areas with low transportation diversity that highlights the impact of transportation diversity on addressing mobility demand. The proposed approach could potentially be used as a benchmark for transportation planning and optimization as well as traffic monitoring and alleviation to allocate resources and adjust the schedule of transit modes in real-time.